| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287288289290291292293294295296297298299300301302303304305306307308309310311312313314315316317318319320321322323324325326327328329330331332333334335336337338339340341342343344345346347348349350351352353354355356357358359360361362363364365366367368369370371372373374375376377378379380381382383384385386387388389390391392393394395396397398399400401402403404405406407408409410411412413414415416417418419420421422423424425426427428429430431432433434435436437438439440441442443444445446447448449450451452453454455456457458459460461462463464465466467468469470471472473474475476477478479480481482483484485486487488489490491492493494495496497498499500501502503504505506507508509510511512513514515516517518519520521522523524525526527528529530531532533534535536537538539540541 | // boost\math\distributions\beta.hpp// Copyright John Maddock 2006.// Copyright Paul A. Bristow 2006.// Use, modification and distribution are subject to the// Boost Software License, Version 1.0.// (See accompanying file LICENSE_1_0.txt// or copy at http://www.boost.org/LICENSE_1_0.txt)// http://en.wikipedia.org/wiki/Beta_distribution// http://www.itl.nist.gov/div898/handbook/eda/section3/eda366h.htm// http://mathworld.wolfram.com/BetaDistribution.html// The Beta Distribution is a continuous probability distribution.// The beta distribution is used to model events which are constrained to take place// within an interval defined by maxima and minima,// so is used extensively in PERT and other project management systems// to describe the time to completion.// The cdf of the beta distribution is used as a convenient way// of obtaining the sum over a set of binomial outcomes.// The beta distribution is also used in Bayesian statistics.#ifndef BOOST_MATH_DIST_BETA_HPP#define BOOST_MATH_DIST_BETA_HPP#include <boost/math/distributions/fwd.hpp>#include <boost/math/special_functions/beta.hpp> // for beta.#include <boost/math/distributions/complement.hpp> // complements.#include <boost/math/distributions/detail/common_error_handling.hpp> // error checks#include <boost/math/special_functions/fpclassify.hpp> // isnan.#include <boost/math/tools/roots.hpp> // for root finding.#if defined (BOOST_MSVC)#  pragma warning(push)#  pragma warning(disable: 4702) // unreachable code// in domain_error_imp in error_handling#endif#include <utility>namespace boost{  namespace math  {    namespace beta_detail    {      // Common error checking routines for beta distribution functions:      template <class RealType, class Policy>      inline bool check_alpha(const char* function, const RealType& alpha, RealType* result, const Policy& pol)      {        if(!(boost::math::isfinite)(alpha) || (alpha <= 0))        {          *result = policies::raise_domain_error<RealType>(            function,            "Alpha argument is %1%, but must be > 0 !", alpha, pol);          return false;        }        return true;      } // bool check_alpha      template <class RealType, class Policy>      inline bool check_beta(const char* function, const RealType& beta, RealType* result, const Policy& pol)      {        if(!(boost::math::isfinite)(beta) || (beta <= 0))        {          *result = policies::raise_domain_error<RealType>(            function,            "Beta argument is %1%, but must be > 0 !", beta, pol);          return false;        }        return true;      } // bool check_beta      template <class RealType, class Policy>      inline bool check_prob(const char* function, const RealType& p, RealType* result, const Policy& pol)      {        if((p < 0) || (p > 1) || !(boost::math::isfinite)(p))        {          *result = policies::raise_domain_error<RealType>(            function,            "Probability argument is %1%, but must be >= 0 and <= 1 !", p, pol);          return false;        }        return true;      } // bool check_prob      template <class RealType, class Policy>      inline bool check_x(const char* function, const RealType& x, RealType* result, const Policy& pol)      {        if(!(boost::math::isfinite)(x) || (x < 0) || (x > 1))        {          *result = policies::raise_domain_error<RealType>(            function,            "x argument is %1%, but must be >= 0 and <= 1 !", x, pol);          return false;        }        return true;      } // bool check_x      template <class RealType, class Policy>      inline bool check_dist(const char* function, const RealType& alpha, const RealType& beta, RealType* result, const Policy& pol)      { // Check both alpha and beta.        return check_alpha(function, alpha, result, pol)          && check_beta(function, beta, result, pol);      } // bool check_dist      template <class RealType, class Policy>      inline bool check_dist_and_x(const char* function, const RealType& alpha, const RealType& beta, RealType x, RealType* result, const Policy& pol)      {        return check_dist(function, alpha, beta, result, pol)          && beta_detail::check_x(function, x, result, pol);      } // bool check_dist_and_x      template <class RealType, class Policy>      inline bool check_dist_and_prob(const char* function, const RealType& alpha, const RealType& beta, RealType p, RealType* result, const Policy& pol)      {        return check_dist(function, alpha, beta, result, pol)          && check_prob(function, p, result, pol);      } // bool check_dist_and_prob      template <class RealType, class Policy>      inline bool check_mean(const char* function, const RealType& mean, RealType* result, const Policy& pol)      {        if(!(boost::math::isfinite)(mean) || (mean <= 0))        {          *result = policies::raise_domain_error<RealType>(            function,            "mean argument is %1%, but must be > 0 !", mean, pol);          return false;        }        return true;      } // bool check_mean      template <class RealType, class Policy>      inline bool check_variance(const char* function, const RealType& variance, RealType* result, const Policy& pol)      {        if(!(boost::math::isfinite)(variance) || (variance <= 0))        {          *result = policies::raise_domain_error<RealType>(            function,            "variance argument is %1%, but must be > 0 !", variance, pol);          return false;        }        return true;      } // bool check_variance    } // namespace beta_detail    // typedef beta_distribution<double> beta;    // is deliberately NOT included to avoid a name clash with the beta function.    // Use beta_distribution<> mybeta(...) to construct type double.    template <class RealType = double, class Policy = policies::policy<> >    class beta_distribution    {    public:      typedef RealType value_type;      typedef Policy policy_type;      beta_distribution(RealType l_alpha = 1, RealType l_beta = 1) : m_alpha(l_alpha), m_beta(l_beta)      {        RealType result;        beta_detail::check_dist(           "boost::math::beta_distribution<%1%>::beta_distribution",          m_alpha,          m_beta,          &result, Policy());      } // beta_distribution constructor.      // Accessor functions:      RealType alpha() const      {        return m_alpha;      }      RealType beta() const      { // .        return m_beta;      }      // Estimation of the alpha & beta parameters.      // http://en.wikipedia.org/wiki/Beta_distribution      // gives formulae in section on parameter estimation.      // Also NIST EDA page 3 & 4 give the same.      // http://www.itl.nist.gov/div898/handbook/eda/section3/eda366h.htm      // http://www.epi.ucdavis.edu/diagnostictests/betabuster.html      static RealType find_alpha(        RealType mean, // Expected value of mean.        RealType variance) // Expected value of variance.      {        static const char* function = "boost::math::beta_distribution<%1%>::find_alpha";        RealType result = 0; // of error checks.        if(false ==            (              beta_detail::check_mean(function, mean, &result, Policy())              && beta_detail::check_variance(function, variance, &result, Policy())            )          )        {          return result;        }        return mean * (( (mean * (1 - mean)) / variance)- 1);      } // RealType find_alpha      static RealType find_beta(        RealType mean, // Expected value of mean.        RealType variance) // Expected value of variance.      {        static const char* function = "boost::math::beta_distribution<%1%>::find_beta";        RealType result = 0; // of error checks.        if(false ==            (              beta_detail::check_mean(function, mean, &result, Policy())              &&              beta_detail::check_variance(function, variance, &result, Policy())            )          )        {          return result;        }        return (1 - mean) * (((mean * (1 - mean)) /variance)-1);      } //  RealType find_beta      // Estimate alpha & beta from either alpha or beta, and x and probability.      // Uses for these parameter estimators are unclear.      static RealType find_alpha(        RealType beta, // from beta.        RealType x, //  x.        RealType probability) // cdf      {        static const char* function = "boost::math::beta_distribution<%1%>::find_alpha";        RealType result = 0; // of error checks.        if(false ==            (             beta_detail::check_prob(function, probability, &result, Policy())             &&             beta_detail::check_beta(function, beta, &result, Policy())             &&             beta_detail::check_x(function, x, &result, Policy())            )          )        {          return result;        }        return ibeta_inva(beta, x, probability, Policy());      } // RealType find_alpha(beta, a, probability)      static RealType find_beta(        // ibeta_invb(T b, T x, T p); (alpha, x, cdf,)        RealType alpha, // alpha.        RealType x, // probability x.        RealType probability) // probability cdf.      {        static const char* function = "boost::math::beta_distribution<%1%>::find_beta";        RealType result = 0; // of error checks.        if(false ==            (              beta_detail::check_prob(function, probability, &result, Policy())              &&              beta_detail::check_alpha(function, alpha, &result, Policy())              &&              beta_detail::check_x(function, x, &result, Policy())            )          )        {          return result;        }        return ibeta_invb(alpha, x, probability, Policy());      } //  RealType find_beta(alpha, x, probability)    private:      RealType m_alpha; // Two parameters of the beta distribution.      RealType m_beta;    }; // template <class RealType, class Policy> class beta_distribution    template <class RealType, class Policy>    inline const std::pair<RealType, RealType> range(const beta_distribution<RealType, Policy>& /* dist */)    { // Range of permissible values for random variable x.      using boost::math::tools::max_value;      return std::pair<RealType, RealType>(static_cast<RealType>(0), static_cast<RealType>(1));    }    template <class RealType, class Policy>    inline const std::pair<RealType, RealType> support(const beta_distribution<RealType, Policy>&  /* dist */)    { // Range of supported values for random variable x.      // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.      return std::pair<RealType, RealType>(static_cast<RealType>(0), static_cast<RealType>(1));    }    template <class RealType, class Policy>    inline RealType mean(const beta_distribution<RealType, Policy>& dist)    { // Mean of beta distribution = np.      return  dist.alpha() / (dist.alpha() + dist.beta());    } // mean    template <class RealType, class Policy>    inline RealType variance(const beta_distribution<RealType, Policy>& dist)    { // Variance of beta distribution = np(1-p).      RealType a = dist.alpha();      RealType b = dist.beta();      return  (a * b) / ((a + b ) * (a + b) * (a + b + 1));    } // variance    template <class RealType, class Policy>    inline RealType mode(const beta_distribution<RealType, Policy>& dist)    {      static const char* function = "boost::math::mode(beta_distribution<%1%> const&)";      RealType result;      if ((dist.alpha() <= 1))      {        result = policies::raise_domain_error<RealType>(          function,          "mode undefined for alpha = %1%, must be > 1!", dist.alpha(), Policy());        return result;      }      if ((dist.beta() <= 1))      {        result = policies::raise_domain_error<RealType>(          function,          "mode undefined for beta = %1%, must be > 1!", dist.beta(), Policy());        return result;      }      RealType a = dist.alpha();      RealType b = dist.beta();      return (a-1) / (a + b - 2);    } // mode    //template <class RealType, class Policy>    //inline RealType median(const beta_distribution<RealType, Policy>& dist)    //{ // Median of beta distribution is not defined.    //  return tools::domain_error<RealType>(function, "Median is not implemented, result is %1%!", std::numeric_limits<RealType>::quiet_NaN());    //} // median    //But WILL be provided by the derived accessor as quantile(0.5).    template <class RealType, class Policy>    inline RealType skewness(const beta_distribution<RealType, Policy>& dist)    {      BOOST_MATH_STD_USING // ADL of std functions.      RealType a = dist.alpha();      RealType b = dist.beta();      return (2 * (b-a) * sqrt(a + b + 1)) / ((a + b + 2) * sqrt(a * b));    } // skewness    template <class RealType, class Policy>    inline RealType kurtosis_excess(const beta_distribution<RealType, Policy>& dist)    {      RealType a = dist.alpha();      RealType b = dist.beta();      RealType a_2 = a * a;      RealType n = 6 * (a_2 * a - a_2 * (2 * b - 1) + b * b * (b + 1) - 2 * a * b * (b + 2));      RealType d = a * b * (a + b + 2) * (a + b + 3);      return  n / d;    } // kurtosis_excess    template <class RealType, class Policy>    inline RealType kurtosis(const beta_distribution<RealType, Policy>& dist)    {      return 3 + kurtosis_excess(dist);    } // kurtosis    template <class RealType, class Policy>    inline RealType pdf(const beta_distribution<RealType, Policy>& dist, const RealType& x)    { // Probability Density/Mass Function.      BOOST_FPU_EXCEPTION_GUARD      static const char* function = "boost::math::pdf(beta_distribution<%1%> const&, %1%)";      BOOST_MATH_STD_USING // for ADL of std functions      RealType a = dist.alpha();      RealType b = dist.beta();      // Argument checks:      RealType result = 0;      if(false == beta_detail::check_dist_and_x(        function,        a, b, x,        &result, Policy()))      {        return result;      }      using boost::math::beta;      return ibeta_derivative(a, b, x, Policy());    } // pdf    template <class RealType, class Policy>    inline RealType cdf(const beta_distribution<RealType, Policy>& dist, const RealType& x)    { // Cumulative Distribution Function beta.      BOOST_MATH_STD_USING // for ADL of std functions      static const char* function = "boost::math::cdf(beta_distribution<%1%> const&, %1%)";      RealType a = dist.alpha();      RealType b = dist.beta();      // Argument checks:      RealType result = 0;      if(false == beta_detail::check_dist_and_x(        function,        a, b, x,        &result, Policy()))      {        return result;      }      // Special cases:      if (x == 0)      {        return 0;      }      else if (x == 1)      {        return 1;      }      return ibeta(a, b, x, Policy());    } // beta cdf    template <class RealType, class Policy>    inline RealType cdf(const complemented2_type<beta_distribution<RealType, Policy>, RealType>& c)    { // Complemented Cumulative Distribution Function beta.      BOOST_MATH_STD_USING // for ADL of std functions      static const char* function = "boost::math::cdf(beta_distribution<%1%> const&, %1%)";      RealType const& x = c.param;      beta_distribution<RealType, Policy> const& dist = c.dist;      RealType a = dist.alpha();      RealType b = dist.beta();      // Argument checks:      RealType result = 0;      if(false == beta_detail::check_dist_and_x(        function,        a, b, x,        &result, Policy()))      {        return result;      }      if (x == 0)      {        return 1;      }      else if (x == 1)      {        return 0;      }      // Calculate cdf beta using the incomplete beta function.      // Use of ibeta here prevents cancellation errors in calculating      // 1 - x if x is very small, perhaps smaller than machine epsilon.      return ibetac(a, b, x, Policy());    } // beta cdf    template <class RealType, class Policy>    inline RealType quantile(const beta_distribution<RealType, Policy>& dist, const RealType& p)    { // Quantile or Percent Point beta function or      // Inverse Cumulative probability distribution function CDF.      // Return x (0 <= x <= 1),      // for a given probability p (0 <= p <= 1).      // These functions take a probability as an argument      // and return a value such that the probability that a random variable x      // will be less than or equal to that value      // is whatever probability you supplied as an argument.      static const char* function = "boost::math::quantile(beta_distribution<%1%> const&, %1%)";      RealType result = 0; // of argument checks:      RealType a = dist.alpha();      RealType b = dist.beta();      if(false == beta_detail::check_dist_and_prob(        function,        a, b, p,        &result, Policy()))      {        return result;      }      // Special cases:      if (p == 0)      {        return 0;      }      if (p == 1)      {        return 1;      }      return ibeta_inv(a, b, p, static_cast<RealType*>(0), Policy());    } // quantile    template <class RealType, class Policy>    inline RealType quantile(const complemented2_type<beta_distribution<RealType, Policy>, RealType>& c)    { // Complement Quantile or Percent Point beta function .      // Return the number of expected x for a given      // complement of the probability q.      static const char* function = "boost::math::quantile(beta_distribution<%1%> const&, %1%)";      //      // Error checks:      RealType q = c.param;      const beta_distribution<RealType, Policy>& dist = c.dist;      RealType result = 0;      RealType a = dist.alpha();      RealType b = dist.beta();      if(false == beta_detail::check_dist_and_prob(        function,        a,        b,        q,        &result, Policy()))      {        return result;      }      // Special cases:      if(q == 1)      {        return 0;      }      if(q == 0)      {        return 1;      }      return ibetac_inv(a, b, q, static_cast<RealType*>(0), Policy());    } // Quantile Complement  } // namespace math} // namespace boost// This include must be at the end, *after* the accessors// for this distribution have been defined, in order to// keep compilers that support two-phase lookup happy.#include <boost/math/distributions/detail/derived_accessors.hpp>#if defined (BOOST_MSVC)# pragma warning(pop)#endif#endif // BOOST_MATH_DIST_BETA_HPP
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